CN111931831B

CN111931831B - Method and system for identifying air interaction group

Info

Publication number: CN111931831B
Application number: CN202010748479.2A
Authority: CN
Inventors: 杨璐
Original assignee: Chinese People's Liberation Army 91776
Current assignee: Chinese People's Liberation Army 91776
Priority date: 2020-07-30
Filing date: 2020-07-30
Publication date: 2022-12-23
Anticipated expiration: 2040-07-30
Also published as: CN111931831A

Abstract

The application discloses a method and a system for identifying an air interaction group, which are used for improving the identification efficiency of the interaction group. The method provided by the application comprises the following steps: determining related evidence information; constructing an evidence matrix according to the evidence information; calculating an evidence value of the evidence matrix; calculating a decision value of a target according to the evidence value; and determining the air interaction group according to the decision value of the target. The application also provides an identification system of the aerial interaction group.

Description

Method and system for identifying air interaction group

Technical Field

The present application relates to the field of target grouping technologies, and in particular, to a method and a system for identifying an air interaction group.

Background

Weapon platforms distributed in different spaces can strike the same target. In order to ensure that the commander can fully recognize the battlefield situation, recognize the situation of the enemy and my, and make a correct operation command decision, the weapon platforms need to be classified according to the targets which the weapon platforms may strike. The identification and differentiation can be classified as an interaction group, belonging to the target grouping problem in the situation awareness field. An interaction group is a group consisting of a plurality of tactically related space groups, each interaction group having a tactical objective and being implemented by the cooperative combat of the plurality of space groups contained therein. In the prior art, subjective judgment of people is mainly relied on, authenticity of evidence is not considered, and identification effectiveness of interaction groups is not high.

Disclosure of Invention

In view of the above technical problems, embodiments of the present application provide a method and a system for identifying an aerial interaction group, so as to obtain a more scientific and reasonable identification result, identify an aerial interaction group more comprehensively and accurately, and improve the identification efficiency of the interaction group.

In one aspect, an identification method for an air interaction group provided in an embodiment of the present application includes:

determining related evidence information;

constructing an evidence matrix according to the evidence information;

calculating an evidence value of the evidence matrix;

calculating a decision value of a target according to the evidence value;

and determining the air interaction group according to the decision value of the target.

Preferably, the constructing an evidence matrix according to the evidence information includes:

setting decision threshold values of various pieces of evidence of the target, and constructing an evidence matrix, wherein N is the number of space group targets to be identified, and M is the number of the evidence of the target to be identified.

Further, the calculating the evidence value of the evidence matrix includes:

determining an evidence validity factor;

and calculating an evidence value of the evidence matrix according to the evidence validity factor.

The determining the evidence validity factor specifically includes:

setting an evidence impact factor matrix L _B×M ＝{l _b,m Wherein B =1,2, \8230, B, M =1,2, \8230, M, B is the number of influencing factors of each evidence;

determining a positive ideal solution

Sum negative ideal solution

Wherein:

respectively calculating Euclidean distances between each item of evidence influence factor and the positive ideal solution and the negative ideal solution:

determining and determining an evidence validity factor C according to the Euclidean distance _m ：

Further, the calculating an evidence value of the evidence matrix according to the evidence validity factor specifically includes:

determining an evidence matrix A _N×M ＝{a _n,m Initial value a of each evidence in _nm N =1,2, \8230, N, M =1,2, \8230, M, more than or equal to zero and less than or equal to 1, N is the number of space group targets to be identified, and M is the number of evidences of the targets to be identified;

when a is _nm At 1, the evidence values are:

when a is _nm At 0, the evidence values are:

wherein,

and taking a value for the mth target evidence corresponding to the nth target to be identified.

The calculating a decision value of the target according to the evidence value comprises:

decision value Z of nth target to be identified _n Determined by the following equation:

where N =1,2, \8230;, N.

Further, the determining an air interaction group according to the decision value of the target specifically includes:

determining a decision judgment threshold H;

according to the decision value Z of the target _n And the decision judgment threshold H is used for judging whether to attack the air defense troop of the party;

and determining all space groups in which targets which are judged to be probably attacked by the air defense troops are positioned as interaction groups.

Further, the decision value Z according to the target _n And the decision judgment threshold H is used for judging whether to attack the air defense troop of the party, and the decision judgment threshold H specifically comprises the following steps:

whether to attack our air defense team is determined by the following formula:

wherein, the decision judgment threshold H is determined by the following formula:

further, after determining the air interaction group, the method further includes:

and tracking and monitoring the aerial interaction groups, and adjusting the aerial interaction groups according to the tracking and monitoring results.

According to the method, the evidence validity factor is introduced to evaluate the authenticity of the evidence, so that a more scientific and reasonable identification result is obtained, the air interaction group is identified more comprehensively and accurately, and the identification efficiency of the interaction group is improved.

Correspondingly, the invention also provides an identification system of the air interaction group, which comprises the following components:

the system comprises a processor, a memory and a collector;

the collector collects information under the control of the processor;

the memory stores a program that can be read and executed by the processor;

the processor, when executing the program, implements one of the methods of identifying all air interaction groups in the method claim.

According to the method and the system, the evidence validity factor is introduced to evaluate the authenticity of the evidence, so that a more scientific and reasonable identification result is obtained, the air interaction group is identified more comprehensively and accurately, and the identification efficiency of the interaction group is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic diagram of a prior art method for clustering species;

FIG. 2 is a schematic diagram of a method for identifying an airborne interaction group according to an embodiment of the present application;

FIG. 3 is a spatial distribution diagram of a target space group according to an embodiment of the present disclosure;

FIG. 4 is a spatial distribution diagram of an enemy air target space group without evidence authenticity factor identification provided by an embodiment of the present application;

FIG. 5 is a spatial distribution diagram of an enemy air target space group identified by considering evidence authenticity factors, provided by an embodiment of the present application;

fig. 6 is a schematic diagram of an identification system of an air interaction group according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.

Some of the words that appear in the text are explained below:

1. the term "and/or" in the embodiments of the present invention describes an association relationship of associated objects, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.

2. In the embodiments of the present application, the term "plurality" means two or more, and other terms are similar thereto.

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The target clustering is to cluster the target objects step by step according to a certain relationship. Typically, the target clustering level may be classified into 5 levels, as shown in fig. 1.

1. Target object group: each individual entity, i.e. each threat unit present in the battlefield.

2. Space group: in the same space, groups are divided according to a certain classification rule. In the same space group, the attributes of all the target objects are consistent, the behaviors are similar, and the positions are similar.

3. Function group: space groups that perform similar functions. Most of the existing literature documents classify functional groups into space groups.

4. Interaction group: a group consisting of multiple tactically related space groups is essentially a group based on the grouping of space groups. Each interaction group has a tactical objective (attack or defense, etc.) that is achieved by the cooperative engagement of the multiple space groups that it contains.

5. Enemy/me/neutral group: all the interaction groups are divided into 3 big groups according to the marks of enemies, I and the middle cube, and three big battle arrays of a battlefield are formed.

As can be seen from fig. 1, the identification of the interaction group needs to take into account a number of factors, such as the target property, the spatial group to which it belongs, the task and the purpose. In the prior art, subjective judgment of people is mainly relied on, authenticity of evidence is not considered, and identification effectiveness of interaction groups is not high.

Aiming at the technical problems, the application provides a method and a system for identifying the air interaction group, which introduce an evidence validity factor to evaluate the authenticity of the evidence, and further adjust a preliminary conclusion on the basis, so that a more scientific and reasonable identification result is obtained, the air interaction group is identified more comprehensively and accurately, and the identification efficiency of the interaction group is improved.

It should be noted that, in the present application, an ideal solution refers to a supposed optimal solution (solution), and each attribute of the solution reaches the optimal value of each alternative solution; while a negative ideal solution refers to the worst solution (solution) assumed, whose respective properties are the worst values of the alternatives.

The method and the system are based on the same application concept, and because the principles of solving the problems of the method and the system are similar, the implementation of the system and the method can be mutually referred, and repeated parts are not repeated.

Various embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the display sequence of the embodiment of the present application only represents the sequence of the embodiment, and does not represent the merits of the technical solutions provided by the embodiments.

Example one

Referring to fig. 2, a schematic diagram of a method for identifying an air interaction group provided in an embodiment of the present application is shown, where the process includes:

s201, determining related evidence information;

aiming at the divided enemy aerial target space group (or function group), a related hypothesis for identifying a target interaction group by judging the consistency of space group target attack attempts is provided, so that various evidence information is obtained.

As a preferred example, target interaction group identification rules and parameter criteria may be further determined that are predicated on the spatial group target attack attempt.

The division of the aerial target space group may be performed by using the method shown in fig. 1, or may be performed according to a set rule according to actual needs, and the present embodiment is not limited to this.

S202, constructing an evidence matrix according to the evidence information;

specifically, firstly, assuming that evidence information is completely true and accurate, an evidence matrix A is constructed by setting decision threshold values of various pieces of evidence of a target and performing corresponding judgment _N×M ＝{a _n,m And f, wherein N is the number of space group targets to be identified, and M is the number of evidences of the targets to be identified.

As a preferred example, M is equal to 9, i.e. the number of evidences that the object to be identified has is 9.

As a preferred example, it can also be based on the evidence matrix A _N×M And carrying out preliminary demonstration analysis, and obtaining preliminary identification conclusions of the target attack attempt and the interaction group through evidence statistics results of the target attack attempt and the non-attack attempt of the space group.

S203, calculating an evidence value of the evidence matrix;

specifically, in order to be closer to the real situation, an evidence validity factor may be set first, and the evidence value of the evidence matrix is calculated according to the evidence validity factor.

As a preferred example, an evidence validity factor c may be set _m ，m＝1,2,…,M，c _m ∈[0,1]Wherein c is _m =0 and c _m =1 represents the highest and lowest degree of evidence validity, i.e. fully valid (trustworthy) and fully invalid (untrustworthy), respectively. Evidence validity factor c _m The determination of (c) can be performed by:

step 1: setting an evidence impact factor matrix L _B×M ＝{l _b,m And the formula is shown in the specification, wherein B =1,2, \8230;, B, M =1,2, \8230;, M and B are influence factor numbers of various evidences. As a preferred example, in setting the impact factor matrix, each impact factor may be normalized and given different weights. The values of the influence factors and the weights may be given by subjective experience, objective methods, or comprehensive approaches, and the specific embodiment is not limited.

Step 2: determining a positive ideal solution

Sum negative ideal solution

Wherein:

step 3, respectively calculating Euclidean distances between each evidence influence factor and the positive ideal solution and the negative ideal solution:

and 4, step 4: determining and determining an evidence validity factor C according to the Euclidean distance _m ：

In addition, c is _m Smaller values indicate higher evidence validity.

Further, each evidence value a in the obtained evidence matrix is set _nm In the [0,1 ]]The inner value, N =1,2, \8230, N, M =1,2, \8230, M, wherein 1 represents a high possibility of attacking me fighting unit, 0 represents a little possibility of attacking me fighting unit, and both 1 and 0 can be clearly distinguished, and 1, 0 and the mean value 0.5 thereof are the distinguishing limit. When the value is 0.5, it is considered to be indistinguishable. In the present embodiment, when the validity and credibility factors are considered,and approaching the value result which is not completely effective and feasible to 0.5.

Specifically, an evidence matrix A is determined _N×M ＝{a _n,m Initial value a of each evidence in _nm N =1,2, \ 8230;, N, M =1,2, \ 8230;, M, and zero or more and 1 or less, in [0, 1;)]An internal value is obtained, wherein 1 represents that attack on the first side is likely to occur, 0 represents that attack on the first side is hardly caused, N is the number of space group targets to be identified, and M is the number of evidences of the targets to be identified; when a is _nm At 1, the evidence values are:

when a is _nm At 0, the evidence values are:

wherein,

In addition, a is _nm When the authenticity of the evidence is not considered, the mth target evidence initial value corresponding to the nth target to be identified is obtained; and then

When the authenticity of the evidence is considered, the mth target evidence value corresponding to the nth target to be identified is obtained.

Through the steps, the evidence matrix under the condition of considering the authenticity of the evidence can be obtained

Wherein N =1,2, \8230;, N, M =1,2, \8230;, M,

each element in (1)

Are still all in [0,1 ]]An internal value.

And S204, calculating a decision value of the target according to the evidence value.

And on the basis of the evaluation of the evidence effectiveness, the evaluation result is applied to an evidence matrix, and a decision value of the target is calculated.

Aiming at each target to be identified, calculating a corresponding decision value according to the corresponding evidence value, wherein the decision value Z of the nth target to be identified _n Determined by the following equation:

wherein N =1,2, \8230;, N:

wherein,

is the mth target evidence value corresponding to the nth target to be recognized determined in S204 when the evidence authenticity is considered. N is the number of space group targets to be identified, and M is the number of evidences of the targets to be identified.

S205, determining the air interaction group according to the decision value of the target.

Specifically, a decision judgment threshold H is determined, and a decision value Z of the target is determined _n And the decision judgment threshold H is used for judging whether to attack the air defense troop of the party;

and determining all space groups in which targets which are judged to be probably attacked by the air defense team are located as interaction groups.

As a preferred example, whether to attack my air defense team can be determined by the following formula:

wherein, the decision judgment threshold H can be determined by the following formula:

as a preferred example, M is 9 and H is 4.5.

As a preferred example, after the above steps are performed, after the aerial interaction group is identified, that is, after all the space groups where the decision is judged to be the targets that are likely to attack (i.e., reach consistency) the air defense force are identified as the interaction group, the tracking is continuously performed, the monitoring is continuously performed, and the dynamic adjustment and the timely adjustment are performed.

Through the steps, an evidence validity factor is introduced to evaluate the authenticity of the evidence, so that a more scientific and reasonable recognition result is obtained, the air interaction group is recognized more comprehensively and accurately, and the recognition efficiency of the interaction group is improved.

The above steps are further illustrated below with reference to specific examples.

4 air target space groups of the air defense combat army facing the enemy are set, and the 4 air target space groups comprise a cruise missile space group, an anti-ship missile space group, a fighter plane space group and a fighter plane space group.

According to the type and information of the air target of the enemy, the cruise missile space group, the anti-ship missile space group, the fighter plane space group and the fighter plane space group are considered to be likely to attack me. The obtained relevant evidence parameters are shown in table 1, and the spatial distribution diagram is shown in fig. 3.

TABLE 1 relevant evidence parameters for enemy air objects

The enemy target is divided into 4 space groups, and the evidence parameter of each space group is the average value of the attribute evidence of each target, as shown in table 2.

TABLE 2 relevant evidence parameters for the enemy aerial target space group

Without considering the authenticity of the evidence (i.e., all complete trustfulness), an evidence matrix is established as shown in table 3:

TABLE 3 Competition hypothesis analysis matrix Table for airborne target attack attempts

Under the condition that all evidences are completely credible, the corresponding evidence value of each target space group to be identified is calculated, a corresponding decision value can be obtained, and then the decision value is compared with the decision judgment threshold value H =4.5, so that the decision vector of the enemy air target space group can be obtained, and the result is shown in table 4. Where 1 means that there is a high possibility of attacking me and 0 means that there is little attack on me.

TABLE 4 decision vectors for identification of enemy aerial target space groups without consideration of evidence authenticity

Name of object	Cruise missile space group	Space group of anti-ship missile	Fighter plane space group	Space group of fighter bombers
					Decision value
	0	1	1	1

According to the analysis results in table 4, it is preliminarily considered that the

space groups

2, 3, and 4 may attack me, and a credibility factor is introduced and evaluated, as shown in table 5.

TABLE 5 identification evidence authenticity analysis matrix table

In the calculation process, the method defines that the scouting ability of our party is insufficient, the enemy unintentionally generates uncertainty, and the enemy intentionally hides true and false as evidence authenticity influence factors, each factor takes an integer value between [0 and 5], 0 and 5 respectively represent the true credibility and the unreal credibility of the evidence, and the solutions of the evidence authenticity influence factors with the values of 0 and 5 are respectively recorded as positive and negative ideal solutions. The adjusted results are shown in Table 6.

Table 6 identification evidence authenticity analysis matrix table

On the basis of setting the evidence authenticity factor, the evidence authenticity factor is added into an enemy aerial target evidence matrix, and after the evidence authenticity factor is compared with a decision judgment threshold value H =4.5, a new decision vector is obtained through comprehensive operation, and the result is shown in Table 7.

TABLE 7 New decision vectors for recognition of enemy aerial target space groups under evidence authenticity considerations

Name of object	Cruise missile space group	Space group of anti-ship missile	Fighter plane space group	Space group of fighter bombers
					Decision value
	0	1	0	1

As shown in table 7, space group 2 and space group 4 are likely to attack my air force, and therefore space group 2 and space group 4 constitute an air interaction group. The results obtained by comparing the analyses of tables 4 and 7 are shown in FIGS. 4 and 5. As can be seen from tables 4 and 7 and fig. 4 and 5, the red space group represents a space group which is likely to attack the air defense army, and under the condition that the evaluation result of the evidence authenticity factor is not introduced, the preliminary conclusion is that the space group which is likely to attack the surface ship army of the same party is the

space group

2, 3 or 4, and under the condition that the evaluation result of the evidence authenticity factor is introduced, the air interaction group is identified by utilizing competitive hypothesis analysis, and the space group which is likely to attack the air defense army is identified as the

space group

2 or 4.

Example two

Based on the same inventive concept, an embodiment of the present invention further provides an identification system for an air interaction group, as shown in fig. 6, the system includes:

comprises a processor 602, a collector 601, a memory 603 and a program which is stored on the memory 603 and can run on the processor 602; the collector 601 is connected to the processor 602 and the memory 603 through a bus interface.

The collector 601 is used for collecting information under the control of the processor;

the processor 602 is configured to read the program in the memory 603, and perform the following processes:

determining related evidence information;

constructing an evidence matrix according to the evidence information;

calculating an evidence value of the evidence matrix;

calculating a decision value of a target according to the evidence value;

It should be noted that in fig. 6, the bus architecture may include any number of interconnected buses and bridges, with one or more processors represented by processor 602 and various circuits represented by memory 603 being linked together. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface. The processor 602 is responsible for managing the bus architecture and general processing, and the memory 603 may store data used by the processor 602 in performing operations.

The processor 602 is further configured to read the program in the memory 603, and when the program is executed, all the methods and steps of the method for identifying an interaction group in an empty space in an embodiment are implemented, and the same parts are not described again.

It should be noted that the system provided in the second embodiment and the method provided in the first embodiment belong to the same inventive concept, and solve the same technical problem to achieve the same technical effect, and the system provided in the second embodiment can implement all the methods in the first embodiment, and the same parts are not described again.

It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation. In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims

1. A method for identifying an airborne interaction group, comprising:

determining related evidence information;

constructing an evidence matrix according to the evidence information;

calculating an evidence value of the evidence matrix;

calculating a decision value of a target according to the evidence value;

determining an aerial interaction group according to the decision value of the target;

the calculating the evidence value of the evidence matrix comprises:

determining an evidence validity factor;

calculating an evidence value of the evidence matrix according to the evidence validity factor;

the determining the evidence validity factor specifically includes:

setting an evidence impact factor matrix L _B×M ＝{l _b,m The formula comprises (a) a plurality of groups of genes, wherein B =1,2, \8230;, B, M =1,2, \8230;, M, B are the number of influencing factors of each evidence;

determining a positive ideal solution

Sum and minus ideal solution

Wherein:

determining an evidence validity factor C according to the Euclidean distance _m ：

Calculating an evidence value of the evidence matrix according to the evidence validity factor specifically includes:

when a is _nm At 1, the evidence values are:

when a is _nm At 0, the evidence values are:

wherein,

is the n-thAnd taking the value of the mth target evidence corresponding to the target to be identified.

2. The method according to claim 1, wherein said constructing an evidence matrix from said evidence information comprises:

setting decision threshold values of all evidences of a target and constructing an evidence matrix A _N×M ＝{a _n,m And f, wherein N is the number of space group targets to be identified, and M is the number of evidences of the targets to be identified.

3. The method of claim 1, wherein the calculating a decision value for a target based on the evidence values comprises:

where N =1,2, \8230;, N.

4. The method of claim 3, wherein determining the air interaction group based on the decision value of the target comprises:

determining a decision judgment threshold H;

5. The method of claim 4, wherein the decision value Z according to the goal is _n And the decision judgment threshold H is used for judging whether to attack the air defense troop of the party, and the decision judgment threshold H specifically comprises the following steps:

whether to attack our air defense team is determined by the following formula:

wherein, the decision judgment threshold H is determined by the following formula: m is the number of evidences that the object to be identified has,

6. the method of any one of claims 1 to 5, wherein after determining the air interaction group, further comprising:

7. An identification system for airborne interaction groups, comprising:

the system comprises a processor, a memory and a collector;

the collector collects information under the control of the processor;

the memory stores a program that can be read and executed by the processor;

the processor, when executing the program, implements a method of identifying air interaction groups as claimed in one of claims 1 to 6.